Clustering XML Documents by Combining Content and Structure

Abstract

XML has become a de facto standard for data representation and exchange over the Internet. With the emergence of more and more XML documents, the clustering of XML documents has become an active research area. XML documents lie between structured data and unstructured data which describe both content and structure, so how to effectively cluster XML documents is a huge challenge. However, most of existing clustering algorithms are based on the structural similarities between XML documents and not or less take into account content of the XML documents. In this paper, we develop a novel method for measuring similarities between XML documents, which effectively combines structure and contents of the XML documents. Based on this similarity model, we adopt hierarchy clustering algorithm to cluster XML documents. The experiments show that this method gains better clustering quality.